clear all

load ParEst_eh1_time0_Mex_nokids1 ParEst_eh1_time0_Mex_nokids1
load ParEst_eh1_time1_Mex_nokids ParEst_eh1_time1_Mex_nokids
load W_time2_age0_eh1_comp01.out
load W_time2_age0_eh1_comp0.out
load W_time2_eh1_comp0.out
load stock_time2_age0_eh1_comp0.out
load stock_time2_eh1_comp0.out

Par1 = zeros(29,1);
Par1(1:24) = ParEst_eh1_time0_Mex_nokids1;
Par1(21) = 10^(ParEst_eh1_time0_Mex_nokids1(21));
Par1(22:24)=1000*ParEst_eh1_time0_Mex_nokids1(22:24);
transition_rates=Par1(1:16); 
Par1(25) = 500*ParEst_eh1_time1_Mex_nokids(1);
Par1(26:29)=ParEst_eh1_time1_Mex_nokids(2:5);

w_f_g=W_time2_age0_eh1_comp01; % Read wages, g and f distributions
wf_1=w_f_g(:,1);        % Wage in formal sector
wi_1=w_f_g(:,2);        % Wage in informal sector
wf_2=w_f_g(:,7);      % Wage in formal sector
wi_2=w_f_g(:,8);      % Wage in informal sector

w_mom=W_time2_age0_eh1_comp0; % Read wage moments
meanwi_1=w_mom(1); meanwf_1=w_mom(2);   meanwi_2=w_mom(3);  meanwf_2=w_mom(4);  sdwi_1=w_mom(5); sdwf_1=w_mom(6);  sdwi_2=w_mom(7);   sdwf_2=w_mom(8);
p10wi_1=w_mom(9);  p10wf_1=w_mom(10); p10wi_2=w_mom(11); p10wf_2=w_mom(12); p25wi_1=w_mom(13); p25wf_1=w_mom(14); p25wi_2=w_mom(15); p25wf_2=w_mom(16); 
p50wi_1=w_mom(17); p50wf_1=w_mom(18); p50wi_2=w_mom(19); p50wf_2=w_mom(20); p75wi_1=w_mom(21); p75wf_1=w_mom(22); p75wi_2=w_mom(23); p75wf_2=w_mom(24); 
p90wi_1=w_mom(25); p90wf_1=w_mom(26); p90wi_2=w_mom(27); p90wf_2=w_mom(28); minwi_1=w_mom(29); minwf_1=w_mom(30); minwi_2=w_mom(31); minwf_2=w_mom(32); 
maxwi_1=w_mom(33); maxwf_1=w_mom(34); maxwi_2=w_mom(35); maxwf_2=w_mom(36);
 
wage_moments_data=[meanwi_1; meanwf_1; meanwi_2; meanwf_2; sdwi_1; sdwf_1; sdwi_2; sdwf_2]; % only using mean and stdev

stock_mom=stock_time2_age0_eh1_comp0(1:9); % Read stocks [FF_h;FI_h;FN_h;IF_h;NF_h;II_h;IN_h;NI_h;NN_h]
stock=stock_mom';
 
HHstates_data=stock; % [FF;FI;FN;IF;NF;II;IN;NI;NN]; % joint-job state


n=50;
 % solve dist of wage offers, value functions and simulate trajectory (MSM)
[Ff_1,ff_1,Fi_1,fi_1,Ff_2,ff_2,Fi_2,fi_2]=solve_wage_offer_dist_2(Par1,wf_1,wi_1,wf_2,wi_2,n);
[Wff,Wfi,Wfn,Wif,Wnf,Wii,Win,Wni,Wnn,iterVF]=solve_value_function_A2(Par1,Ff_1,wf_1,Fi_1,wi_1,Ff_2,wf_2,Fi_2,wi_2,n);
[HHstates,wage_moments,transitions]=data_simulation_A12_end(Par1,ff_1,wf_1,fi_1,...
    wi_1,ff_2,wf_2,fi_2,wi_2,Wff,Wfi,Wfn,Wif,Wnf,Wii,Win,Wni,Wnn);


%Contact rates
Transitions_both = {'F-N'; 'I-N'; 'N-F'; 'N-I'; 'F-I'; 'I-F'; 'p1'; 'q1';''; 'F-N'; 'I-N'; 'N-F'; 'N-I'; 'F-I'; 'I-F'; 'p2'; 'q2'};
Estimates = [Par1(1); Par1(2); Par1(3); Par1(4); Par1(5); Par1(6); Par1(13); Par1(14);NaN;Par1(7); Par1(8); Par1(9); Par1(10); Par1(11); Par1(12); Par1(15); Par1(16)];
Transition_Rates_table = table(Transitions_both, Estimates);
writetable(Transition_Rates_table, 'Transition_Rates_table.xls')


alphaf=Par1(17);
betaf=Par1(18);
alphai=Par1(19);
betai=Par1(20);
theta=Par1(21);
a=Par1(22);
b1 = Par1(23); 
b2 = Par1(24);
gamma = Par1(25);
alphaf_2=Par1(26);
betaf_2=Par1(27);
alphai_2=Par1(28);
betai_2=Par1(29);

HH_avg_Inc = p50wi_1; % median wage of informal men
MWP_gamma = gamma/(exp(-theta*HH_avg_Inc));
save MWP_gamma MWP_gamma
load MWP_a MWP_a

%Preference parameters
Preference = {'theta';'b1';'b2';'a';'MWP a';'gamma';'MWP gamma'};
Estimates = [theta; b1; b2; a; MWP_a; gamma; MWP_gamma];
Preferences_table = table(Preference, Estimates);
writetable(Preferences_table, 'Preferences_table.xls')

%Wage offer parameters
Wage_offer = {'alpha_formal'; 'beta_formal';'alpha_informal';'beta_informal'};
Estimates = [alphaf; betaf; alphai; betai];
Wage_offer_par_table = table(Wage_offer, Estimates);
writetable(Wage_offer_par_table, 'Wage_offer_par_table.xls')

% Generate mean LOG WAGES - F distribution 
mean_wf_1f=log(sum(wf_1.*ff_1));
mean_wi_1f=log(sum(wi_1.*fi_1));
mean_wf_2f=log(sum(wf_2.*ff_2));
mean_wi_2f=log(sum(wi_2.*fi_2));
mean_wage_offer_time1=[mean_wf_1f;mean_wi_1f;NaN;mean_wf_2f;mean_wi_2f];
save mean_wage_offer_time1 mean_wage_offer_time1

%Wage offer parameters
Wage_offer = {'alpha_formal';'beta_formal';'alpha_informal';'beta_informal';'';'mean_wf_1f';'mean_wi_1f';NaN;'mean_wf_2f';'mean_wi_2f'};
Estimates = [alphaf_2; betaf_2; alphai_2; betai_2;NaN;mean_wage_offer_time1];
Wage_offer_par_table = table(Wage_offer, Estimates);
writetable(Wage_offer_par_table, 'Wage_offer_par_table_2nd_stage.xls')

x=wage_moments_data;
wage_moments_data1=[x(2);x(6);NaN;NaN;...	
x(1);x(5);NaN;NaN;...
x(4);x(8);NaN;NaN;...	
x(3);x(7)];
w=wage_moments(1:8);
wage_moments1=[w(2);w(6);NaN;NaN;... 
w(1);w(5);NaN;NaN;...
w(4);w(8);NaN;NaN;... 
w(3);w(7)];
% Model fit (for paper)
Model_fit_labels = {'mff'; 'mfi'; 'mfn'; 'mif'; 'mnf'; 'mii'; 'min'; 'mni'; 'mnn';'';'';'meanwf_1'; 'sdwf_1';'';''; 'meanwi_1'; 'sdwi_1';'';'';...
    'meanwf_2'; 'sdwf_2';'';''; 'meanwi_2'; 'sdwi_2'};
ModelFit_actual=[HHstates_data;NaN;NaN;log(wage_moments_data1)];
ModelFit_model=[HHstates;NaN;NaN;log(wage_moments1)];
Model_fit_table = table(Model_fit_labels,ModelFit_actual,ModelFit_model);
writetable(Model_fit_table, 'Model_fit_table_paper.xls')
